Backend Engineer - Remote

Role overview

Backend Engineer (Remote), part-time (30–40 hours/week). You’ll design and build backend/distributed infrastructure to train, deploy, and scale AI agents on high-performance compute environments.

What you’ll be doing

• Design, build, and optimize distributed infrastructure for AI agent training, deployment, and scaling
• Develop core backend systems: services, APIs, and orchestration layers for agent lifecycles
• Support tool execution, memory access, and multi-agent coordination
• Collaborate with research and applied AI teams to integrate model-serving pipelines and agent reasoning loops into production
• Build and maintain agent runtime infrastructure:
  • task scheduling
  • state management
  • inter-agent communication
  • execution reliability
• Implement monitoring, observability, and fault tolerance for long-running agent processes and distributed workflows
• Evaluate and improve performance across compute, networking, storage, and inference layers; identify and resolve bottlenecks
• Participate in synchronous collaboration sessions (4-hour windows, 2–3 times/week) to review architecture, troubleshoot distributed systems, and iterate on designs

Requirements

• Strong foundation in Computer Science, Software Engineering, or Systems Design
• Experience building large-scale distributed systems
• Proficiency in one or more backend/systems languages: Go, Rust, Python, C++, Java, Scala, C#, Kotlin, TypeScript/JavaScript
• Experience with cloud infrastructure (AWS, GCP, or Azure)
• Experience with containerization/orchestration: Docker and Kubernetes
• Strong production experience designing backend services, APIs, and distributed systems
• Knowledge of networking, data streaming, caching, and performance optimization in distributed systems
• Excellent collaboration and communication skills
• Ability to commit 30–40 hours/week, including required synchronous sessions

Nice to have

• Familiarity with LLM inference pipelines, agent frameworks, multi-agent architectures, or reinforcement learning environments